Computing system with a cross-locale natural language searching mechanism and method of operation thereof

ABSTRACT

A computing system comprising: a control unit configured to: receive an input request for a point of interest; determine a first linguistic context for the input request based on one or more input request characteristics, a user profile, a location, and a first connotation database; translate the input request to a second linguistic context based on a translation flag and a second connotation database, wherein the second connotation database is mapped to the first connotation database; and a user interface, coupled to the control unit, configured to display a translation result for the input request based on the first linguistic context or the second linguistic context.

TECHNICAL FIELD

An embodiment of the present invention relates generally to a computingsystem, and more particularly to a computing system with a cross-localenatural language searching mechanism.

BACKGROUND

Modern consumer and industrial electronics, especially devices such ascellular phones, smart phones, tablet computers, vehicle integratedcomputing and communication systems, portable digital assistants, andcombination devices, are providing increasing levels of functionality tosupport modern life including communication services. Research anddevelopment in the existing technologies can take a myriad of differentdirections.

Location based applications offer a typical portfolio of servicesincluding: navigation, map lookup and display, and local business andpoint of interest search. These services are naturally tied together inthat they are all location-based and assume that these services operatewithin a locale shared between a user and real-world objects ofreference. That is to say that if the user is physically within theUnited States, then applications tend to assume that because the primarylanguage within the United States is U.S. English, the user will want tonavigate to locations named and expressed in U.S. English, ask to viewmaps of U.S. locations displayed with labels written in U.S. English,hear feedback spoken or displayed in U.S. English, and search forbusinesses and points of interest using names and concepts drawn fromU.S. English. However, this assumption does not hold for everyone, forexample, in the United States who is learning U.S. English or does notspeak U.S. English at all. Thus, a need still remains to translatesearch terms from a user's native language into semantically equivalentsearch terms in a language associated with the data locale and insertthis translation step between the search acceptance and result displaystages of the search request processing.

Solutions to these problems have been long sought but prior developmentshave not taught or suggested any solutions and, thus, solutions to theseproblems have long eluded those skilled in the art.

SUMMARY

An embodiment of the present invention provides a computing systemcomprising: a control unit configured to: receive an input request for apoint of interest; determine a first linguistic context for the inputrequest based on one or more input request characteristics, a userprofile, a location, and a first connotation database; translate theinput request to a second linguistic context based on a translation flagand a second connotation database, wherein the second connotationdatabase is mapped to the first connotation database; and a userinterface, coupled to the control unit, configured to display atranslation result for the input request based on the first linguisticcontext or the second linguistic context.

An embodiment of the present invention provides a computing systemcomprising: a first control unit configured to: receive an input requestfor a point of interest; determine a first linguistic context for theinput request based on one or more input request characteristics, a userprofile, a location, and a first connotation database; a communicationunit, coupled to the first control unit, configured to: send atransmission of the input request to a second control unit based on atranslation flag; receive a translation result for the input requestbased on a translation of the input request to a second linguisticcontext by the second control unit; the second control unit, coupled tothe communication unit, configured to translate the input request to thesecond linguistic context based on the translation flag and a secondconnotation database, wherein the second connotation database is mappedto the first connotation database; and a user interface, coupled to thefirst control unit, configured to display a translation result for theinput request based on the first linguistic context or the secondlinguistic context.

An embodiment of the present invention provides a method of operating acomputing system comprising: receiving an input request for a point ofinterest; determining a first linguistic context for the input requestbased on one or more input request characteristics, a user profile, alocation, and a first connotation database translating the input requestto a second linguistic context based on a translation flag and a secondconnotation database, wherein the second connotation database is mappedto the first connotation database; and displaying a translation resultfor the input request based on the first linguistic context or thesecond linguistic context.

An embodiment of the present invention provides a non-transitorycomputer readable medium including instructions for operating acomputing system comprising: receiving an input request for a point ofinterest; determining a first linguistic context for the input requestbased on one or more input request characteristics, a user profile, alocation, and a first connotation database; translating the inputrequest to a second linguistic context based on a translation flag and asecond connotation database, wherein the second connotation database ismapped to the first connotation database; and displaying a translationresult for the input request based on the first linguistic context orthe second linguistic context.

Certain embodiments of the invention have other steps or elements inaddition to or in place of those mentioned above. The steps or elementswill become apparent to those skilled in the art from a reading of thefollowing detailed description when taken with reference to theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a computing system with a cross-locale natural languagesearching mechanism in an embodiment of the present invention.

FIG. 2 is an exemplary block diagram of the components of the computingsystem.

FIG. 3 is an example of a display interface of the computing system.

FIG. 4 is an exemplary control flow of the computing system.

FIG. 5 is an exemplary representation of a cognitive synonym space forthe computing system.

FIG. 6 is a flow chart of a method of operation of the computing systemin a further embodiment of the present invention.

DETAILED DESCRIPTION

The following embodiments are described in sufficient detail to enablethose skilled in the art to make and use the invention. It is to beunderstood that other embodiments would be evident based on the presentdisclosure, and that system, process, or mechanical changes may be madewithout departing from the scope of an embodiment of the presentinvention.

In the following description, numerous specific details are given toprovide a thorough understanding of the invention. However, it will beapparent that the invention may be practiced without these specificdetails. In order to avoid obscuring an embodiment of the presentinvention, some well-known circuits, system configurations, and processsteps are not disclosed in detail.

The drawings showing embodiments of the system are semi-diagrammatic,and not to scale and, particularly, some of the dimensions are for theclarity of presentation and are shown exaggerated in the drawingfigures. Similarly, although the views in the drawings for ease ofdescription generally show similar orientations, this depiction in thefigures is arbitrary for the most part. Generally, the invention can beoperated in any orientation.

The term “vehicle” referred to herein can include cars, self-drivingcars, trains, buses, bicycles, boats, motorcycles, airplanes,helicopters, or any other mode of transport, or a combination thereof inan embodiment of the present invention in accordance with the context inwhich the term is used.

The term “module” or “unit” referred to herein can include software,hardware, or a combination thereof in an embodiment of the presentinvention in accordance with the context in which the term is used. Forexample, the software can be machine code, firmware, embedded code, andapplication software. Also for example, the hardware can be circuitry,processor, computer, integrated circuit, integrated circuit cores, apressure sensor, an inertial sensor, a microelectromechanical system(MEMS), passive devices, or a combination thereof. Further, if a moduleis written in the system claims section below, the modules are deemed toinclude hardware circuitry for the purposes and the scope of systemclaims.

The modules in the following description of the embodiments can becoupled to one other as described or as shown. The coupling can bedirect or indirect without or with, respectively, intervening itemsbetween coupled items. The coupling can be by physical contact or bycommunication between items.

Referring now to FIG. 1, therein is shown a computing system 100 with across-locale natural language searching mechanism in a first embodimentof the present invention. The computing system 100 includes a firstdevice 102, such as a client or a server, connected to a second device106, such as a client or server. The first device 102 can communicatewith the second device 106 with a communication path 104, such as awireless or wired network.

For example, the first device 102 can be of any of a variety of devices,such as a smart phone, cellular phone, personal digital assistant,tablet computer, a notebook computer, laptop computer, desktop computer,or a vehicle integrated communication system. The first device 102 cancouple, either directly or indirectly, to the communication path 104 tocommunicate with the second device 106 or can be a stand-alone device.The first device 102 can be incorporated in a vehicle.

The second device 106 can be any of a variety of centralized ordecentralized computing devices. For example, the second device 106 canbe a laptop computer, a desktop computer, grid-computing resources, avirtualized computer resource, cloud computing resources, routers,switches, peer-to-peer distributed computing devices, a server, or acombination thereof. The second device 106 can be centralized in asingle room, distributed across different rooms, distributed acrossdifferent geographical locations, embedded within a telecommunicationsnetwork. The second device 106 can couple with the communication path104 to communicate with the first device 102. The second device 106 canbe incorporated in a vehicle.

For illustrative purposes, the computing system 100 is shown with thefirst device 102 as a client device, although it is understood that thecomputing system 100 can have the first device 102 as a different typeof device. For example, the first device 102 can be a server. Also forillustrative purposes, the computing system 100 is shown with the seconddevice 106 as a server, although it is understood that the computingsystem 100 can have the second device 106 as a different type of device.For example, the second device 106 can be a client device.

For brevity of description in the embodiments discussed below, the firstdevice 102 will be described as a client device and the second device106 will be described as a server device. The embodiments of the presentinvention, however, are not limited to this selection for the type ofdevices. The selection is an example of an embodiment of the presentinvention.

Also for illustrative purposes, the computing system 100 is shown withthe second device 106 and the first device 102 as end points of thecommunication path 104, although it is understood that the computingsystem 100 can have a different partition between the first device 102,the second device 106, and the communication path 104. For example, thefirst device 102, the second device 106, or a combination thereof canalso function as part of the communication path 104.

The communication path 104 can span and represent a variety of networksand network topologies. For example, the communication path 104 caninclude wireless communication, wired communication, opticalcommunication, ultrasonic communication, or the combination thereof. Forexample, satellite communication, cellular communication, Bluetooth,Infrared Data Association standard (IrDA), wireless fidelity (WiFi), andworldwide interoperability for microwave access (WiMAX) are examples ofwireless communication that can be included in the communication path104. Cable, Ethernet, digital subscriber line (DSL), fiber optic lines,fiber to the home (FTTH), and plain old telephone service (POTS) areexamples of wired communication that can be included in thecommunication path 104. Further, the communication path 104 can traversea number of network topologies and distances. For example, thecommunication path 104 can include direct connection, personal areanetwork (PAN), local area network (LAN), metropolitan area network(MAN), wide area network (WAN), or a combination thereof.

Referring now to FIG. 2, therein is shown an exemplary block diagram ofthe components of the computing system 100. The first device 102 cansend information in a first device transmission 222 over thecommunication path 104 to the second device 106. The second device 106can send information in a second device transmission 224 over thecommunication path 104 to the first device 102. The first devicetransmission 222 and the second device transmission 224 can be sent overone or more communication channels 248. A communication channel 248refers either to a physical transmission medium such as a wire, or to alogical connection over a multiplexed medium such as a radio channel.

For illustrative purposes, the computing system 100 is shown with thefirst device 102 as a client device, although it is understood that thecomputing system 100 can have the first device 102 as a different typeof device. For example, the first device 102 can be a server.

Also for illustrative purposes, the computing system 100 is shown withthe second device 106 as a server, although it is understood that thecomputing system 100 can have the second device 106 as a different typeof device. For example, the second device 106 can be a client device.

For brevity of description in this embodiment of the present invention,the first device 102 will be described as a client device and the seconddevice 106 will be described as a server device. The embodiment of thepresent invention is not limited to this selection for the type ofdevices. The selection is an example of an embodiment of the presentinvention.

The first device 102 can include a first control unit 210, a firststorage unit 216, a first communication unit 202, a first user interface254, and a first location unit 214. The first control unit 210 caninclude a first control interface 212. The first control unit 210 canexecute a first software 220 to provide the intelligence of thecomputing system 100. The first control unit 210 can be implemented in anumber of different ways. For example, the first control unit 210 can bea processor, an application specific integrated circuit (ASIC), anembedded processor, a microprocessor, a hardware control logic, ahardware finite state machine (FSM), a digital signal processor (DSP),or a combination thereof.

The first control interface 212 can be used for communication betweenthe first control unit 210 and other functional units in the firstdevice 102. The first control interface 212 can also be used forcommunication that is external to the first device 102. The firstcontrol interface 212 can receive information from the other functionalunits or from external sources, or can transmit information to the otherfunctional units or to external destinations. The external sources andthe external destinations refer to sources and destinations external tothe first device 102.

The first control interface 212 can be implemented in different ways andcan include different implementations depending on which functionalunits or external units are being interfaced with the first controlinterface 212. For example, the first control interface 212 can beimplemented with a pressure sensor, an inertial sensor, amicroelectromechanical system (MEMS), optical circuitry, waveguides,wireless circuitry, wireline circuitry, application programminginterface, or a combination thereof.

The first storage unit 216 can store the first software 220. Forillustrative purposes, the first storage unit 216 is shown as a singleelement, although it is understood that the first storage unit 216 canbe a distribution of storage elements. Also for illustrative purposes,the computing system 100 is shown with the first storage unit 216 as asingle hierarchy storage system, although it is understood that thecomputing system 100 can have the first storage unit 216 in a differentconfiguration. For example, the first storage unit 216 can be formedwith different storage technologies forming a memory hierarchal systemincluding different levels of caching, main memory, rotating media, oroff-line storage.

The first storage unit 216 can be a volatile memory, a nonvolatilememory, an internal memory, an external memory, or a combinationthereof. For example, the first storage unit 216 can be a nonvolatilestorage such as non-volatile random access memory (NVRAM), Flash memory,disk storage, or a volatile storage such as static random access memory(SRAM).

The first storage unit 216 can include a first storage interface 218.The first storage interface 218 can be used for communication betweenthe first storage unit 216 and other functional units in the firstdevice 102. The first storage interface 218 can also be used forcommunication that is external to the first device 102. The firststorage interface 218 can receive information from the other functionalunits or from external sources, or can transmit information to the otherfunctional units or to external destinations. The external sources andthe external destinations refer to sources and destinations external tothe first device 102.

The first storage interface 218 can include different implementationsdepending on which functional units or external units are beinginterfaced with the first storage unit 216. The first storage interface218 can be implemented with technologies and techniques similar to theimplementation of the first control interface 212.

The first communication unit 202 can enable external communication toand from the first device 102. For example, the first communication unit202 can permit the first device 102 to communicate with the seconddevice 106 of FIG. 1, an attachment, such as a peripheral device or acomputer desktop, and the communication path 104.

The first communication unit 202 can also function as a communicationhub allowing the first device 102 to function as part of thecommunication path 104 and not limited to be an end point or terminalunit to the communication path 104. The first communication unit 202 caninclude active and passive components, such as microelectronics or anantenna, for interaction with the communication path 104.

The first communication unit 202 can include a first communicationinterface 208. The first communication interface 208 can be used forcommunication between the first communication unit 202 and otherfunctional units in the first device 102. The first communicationinterface 208 can receive information from the other functional units orfrom external sources, or can transmit information to the otherfunctional units or to external destinations. The external sources andthe external destinations refer to sources and destinations external tothe first device 102.

The first communication interface 208 can include differentimplementations depending on which functional units are being interfacedwith the first communication unit 202. The first communication interface208 can be implemented with technologies and techniques similar to theimplementation of the first control interface 212.

The first communication unit 202 can couple with the communication path104 to send information to the second device 106 in the first devicetransmission 222. The second device 106 can receive information in asecond communication unit 226 from the first device transmission 222 ofthe communication path 104.

The first control unit 210 can operate the first user interface 254 topresent information generated by the computing system 100. The firstuser interface 254, in one embodiment, allows a user of the computingsystem 100 to interface with the first device 102. The first userinterface 254 can include an input device and an output device. Examplesof the input device of the first user interface 254 can include akeypad, a touchpad, soft-keys, a keyboard, a microphone, sensors forreceiving remote signals, or any combination thereof to provide data andcommunication inputs. Examples of the output device can include a firstdisplay interface 206 and a first audio interface 204.

The first control unit 210 can operate the first user interface 254 topresent information generated by the computing system 100. The firstcontrol unit 210 can also execute the first software 220 for the otherfunctions of the computing system 100. The first control unit 210 canfurther execute the first software 220 for interaction with thecommunication path 104 via the first communication unit 202.

The first display interface 206 can be any graphical user interface suchas a display, a projector, a video screen, or any combination thereof.The first audio interface 204 can include sensors, speakers,microphones, headphones, subwoofers, surround sound components,transducers, or any combination thereof. The first display interface 206and the first audio interface 204 allow a user of the computing system100 to interact with the computing system 100.

The first location unit 214 can generate location information, currentheading, and current speed of the first device 102, as examples. Thefirst location unit 214 can be implemented in many ways. For example,the first location unit 214 can function as at least a part of a globalpositioning system (GPS) and can include components, such as a GPSreceiver, an inertial navigation system, a cellular-tower locationsystem, a pressure location system, or any combination thereof.

The first location unit 214 can include a first location interface 250.The first location interface 250 can be used for communication betweenthe first location unit 214 and other functional units in the firstdevice 102. The first location interface 250 can also be used forcommunication that is external to the first device 102. The firstlocation interface 250 can be implemented with technologies andtechniques similar to the implementation of the first control interface212.

The second device 106 can be optimized for implementing an embodiment ofthe present invention in a multiple device embodiment with the firstdevice 102. The second device 106 can provide additional or higherperformance processing power compared to the first device 102. Thesecond device 106 can include a second control unit 238, a secondstorage unit 240, a second communication unit 226, a second userinterface 228, and a second location unit 246.

The second control unit 238 can include a second control interface 236.The second control unit 238 can execute a second software 244 to providethe intelligence of the computing system 100. The second software 244can also operate independently or in conjunction with the first software220. The second control unit 238 can provide additional performancecompared to the first control unit 210.

The second control unit 238 can be implemented in a number of differentways. For example, the second control unit 238 can be a processor, anapplication specific integrated circuit (ASIC), an embedded processor, amicroprocessor, a hardware control logic, a hardware finite statemachine (FSM), a digital signal processor (DSP), or a combinationthereof.

The second control interface 236 can be used for communication betweenthe second control unit 238 and other functional units in the seconddevice 106. The second control interface 236 can also be used forcommunication that is external to the second device 106. The secondcontrol interface 236 can receive information from the other functionalunits or from external sources, or can transmit information to the otherfunctional units or to external destinations. The external sources andthe external destinations refer to sources and destinations external tothe second device 106.

The second control interface 236 can be implemented in different waysand can include different implementations depending on which functionalunits or external units are being interfaced with the second controlinterface 236. For example, the second control interface 236 can beimplemented with a pressure sensor, an inertial sensor, amicroelectromechanical system (MEMS), optical circuitry, waveguides,wireless circuitry, wireline circuitry, application programminginterface, or a combination thereof.

The second storage unit 240 can store the second software 244. Thesecond storage unit 240 can be sized to provide the additional storagecapacity to supplement the first storage unit 216. For illustrativepurposes, the second storage unit 240 is shown as a single element,although it is understood that the second storage unit 240 can be adistribution of storage elements. Also for illustrative purposes, thecomputing system 100 is shown with the second storage unit 240 as asingle hierarchy storage system, although it is understood that thecomputing system 100 can have the second storage unit 240 in a differentconfiguration. For example, the second storage unit 240 can be formedwith different storage technologies forming a memory hierarchal systemincluding different levels of caching, main memory, rotating media, oroff-line storage.

The second storage unit 240 can be a volatile memory, a nonvolatilememory, an internal memory, an external memory, or a combinationthereof. For example, the second storage unit 240 can be a nonvolatilestorage such as non-volatile random access memory (NVRAM), Flash memory,disk storage, or a volatile storage such as static random access memory(SRAM).

The second storage unit 240 can include a second storage interface 242.The second storage interface 242 can be used for communication betweenthe second storage unit 240 and other functional units in the seconddevice 106. The second storage interface 242 can also be used forcommunication that is external to the second device 106. The secondstorage interface 242 can receive information from the other functionalunits or from external sources, or can transmit information to the otherfunctional units or to external destinations. The external sources andthe external destinations refer to sources and destinations external tothe second device 106.

The second storage interface 242 can include different implementationsdepending on which functional units or external units are beinginterfaced with the second storage unit 240. The second storageinterface 242 can be implemented with technologies and techniquessimilar to the implementation of the second control interface 236.

The second communication unit 226 can enable external communication toand from the second device 106. For example, the second communicationunit 226 can permit the second device 106 to communicate with the firstdevice 102 of FIG. 1, an attachment, such as a peripheral device or acomputer desktop, and the communication path 104.

The second communication unit 226 can also function as a communicationhub allowing the second device 106 to function as part of thecommunication path 104 and not limited to be an end point or terminalunit to the communication path 104. The second communication unit 226can include active and passive components, such as microelectronics oran antenna, for interaction with the communication path 104.

The second communication unit 226 can include a second communicationinterface 230. The second communication interface 230 can be used forcommunication between the second communication unit 226 and otherfunctional units in the second device 106. The second communicationinterface 230 can receive information from the other functional units orfrom external sources, or can transmit information to the otherfunctional units or to external destinations. The external sources andthe external destinations refer to sources and destinations external tothe second device 106.

The second communication interface 230 can include differentimplementations depending on which functional units are being interfacedwith the second communication unit 226. The second communicationinterface 230 can be implemented with technologies and techniquessimilar to the implementation of the second control interface 236.

The second communication unit 226 can couple with the communication path104 to send information to the first device 102 in the second devicetransmission 224. The first device 102 can receive information in thefirst communication unit 202 from the second device transmission 224 ofthe communication path 104

The second control unit 238 can operate the second user interface 228 topresent information generated by the computing system 100. The seconduser interface 228, in one embodiment, allows a user of the computingsystem 100 to interface with the second device 106. The second userinterface 228 can include an input device and an output device. Examplesof the input device of the second user interface 228 can include akeypad, a touchpad, soft-keys, a keyboard, a microphone, sensors forreceiving remote signals, or any combination thereof to provide data andcommunication inputs. Examples of the output device can include a seconddisplay interface 234 and a second audio interface 232.

The second control unit 238 can operate the second user interface 228 topresent information generated by the computing system 100. The secondcontrol unit 238 can also execute the second software 244 for the otherfunctions of the computing system 100. The second control unit 238 canfurther execute the second software 244 for interaction with thecommunication path 104 via the second communication unit 226.

The second display interface 234 can be any graphical user interfacesuch as a display, a projector, a video screen, or any combinationthereof. The second audio interface 232 can include sensors, speakers,microphones, headphones, subwoofers, surround sound components,transducers, or any combination thereof. The second display interface234 and the second audio interface 232 allow a user of the computingsystem 100 to interact with the computing system 100.

The second location unit 246 can generate location information, currentheading, and current speed of the second device 106, as examples. Thesecond location unit 246 can be implemented in many ways. For example,the second location unit 246 can function as at least a part of a globalpositioning system (GPS) and can include components, such as a GPSreceiver, an inertial navigation system, a cellular-tower locationsystem, a pressure location system, or any combination thereof.

The second location unit 246 can include a second location interface252. The second location interface 252 can be used for communicationbetween the second location unit 246 and other functional units in thesecond device 106. The second location interface 252 can also be usedfor communication that is external to the second device 106. The secondlocation interface 252 can be implemented with technologies andtechniques similar to the implementation of the second control interface236.

Functionality of the computing system 100 can be provided by the firstcontrol unit 210, the second control unit 238, or a combination thereof.For illustrative purposes, the second device 106 is shown with thepartition having the second user interface 228, the second storage unit240, the second control unit 238, a second location unit 246, and thesecond communication unit 226, although it is understood that the seconddevice 106 can have a different partition. For example, the secondsoftware 244 can be partitioned differently such that some or all of itsfunction can be in the second control unit 238 and the secondcommunication unit 226. Also, the second device 106 can include otherfunctional units not shown in FIG. 2 for clarity.

The first device 102 can have a similar or different partition as thesecond device 106. The functional units in the first device 102 can workindividually and independently of the other functional units. The firstdevice 102 can work individually and independently from the seconddevice 106 and the communication path 104. The functional units in thesecond device 106 can work individually and independently of the otherfunctional units. The second device 106 can work individually andindependently from the first device 102 and the communication path 104.

For illustrative purposes, the computing system 100 is described byoperation of the first device 102 and the second device 106. It isunderstood that the first device 102 and the second device 106 canoperate any of the modules, units, and functions of the computing system100.

Referring now to FIG. 3, therein is shown an example of the first userinterface 254 of the first device 102 or the second user interface 228of the second device 106 of FIG. 1. For brevity of description in thisembodiment, reference to the first user interface 254 will be made,however, the descriptions with respect to the first user interface 254can be similarly applicable to the second user interface 228.

In one embodiment, the first user interface 254 includes the firstdisplay interface 206. The first display interface 206 can enable aninput request 306 for a point of interest 310 using a search box 302.The input request 306 can include any manner of inputting a searchrequest for the point of interest 310. The input request 306 can be anyway by which a system user 304 can search for the point of interest 310,including but not limited to, searching using alpha-numeric characters,symbols, voice commands, gestures, or a combination thereof. The searchbox 302 can enable searching for the point of interest 310 using anysearch engine techniques, such as those used in a desktop search engineor a web search engine. Details of the search mechanism for the point ofinterest 310 will be discussed in greater detail below.

The point of interest 310 is a physical location that a system user 304finds useful or interesting, or that a system user 304 or others mightconsider be particularly affiliating with or tied to a geographic area.For example, a point of interest 310 may be a store, a landmark, anoffice building or site, a park, an address, a point on a map, oranother attraction that is popular among people of a geographic area.

Continuing with the example, the input request 306 can be input into thesearch box 302 using one or more languages. For example, the inputrequest 306 can be input into the search box 302 in a system user'slanguage 314. The system user's language 314 is a language understoodby, spoken by, or native to the system user 304. As an example, thesystem user's language 314 can be designated by the system user 304.Also as an example, the system user's language 314 can be assignedautomatically by the computing system 100 based on one or morecharacteristics of the input request 306. The one or morecharacteristics of the input request 306 refers to a linguistic propertyof the input request 306 and can include, for example, a syntax of theinput request 306, language characters associated with the input request306, a dialect designation of the input request 306, a sentencestructure of the input request 306, a grammar of the input request 306,a linguistic pattern of the input request 306, phonemes of the inputrequest 306, or any combination thereof.

The input request 306 can be in the same language or a differentlanguage as the system user's language 314 or the language associatedwith the system user's 304 current location 308. For example, if thesystem user's language 314 is assigned or designated to be “MexicanSpanish,” the input request 306 can be input into the search box 302using “Mexican Spanish” syntax, words, or phrases, despite the systemuser's 304 current location 308 being in, for example, Toronto, Canada,where the primary language is “Canadian English,” and in which thepoints of interest 310 are typically designated in “Canadian English.”In another example, if the system user's language 314 is assigned ordesignated to be “Mexican Spanish,” the input request 306 can be inputinto the search box 302 using “Brazilian Portuguese” despite the systemuser's 304 current location 308 being in, for example, Toronto, Canada.The system user's language 314 can be associated with a profileassociated with the system user 304. The system user's language 314designation can be stored in the first storage unit 216, the secondstorage unit 240, or a combination thereof.

Continuing with the example, the input request 306 can be received bythe computing system 100 in order for the computing system 100 to searchfor the point of interest 310 corresponding to the input request 306,either on the first device 102, the second device 106, or a combinationthereof. Once received, the computing system 100 can search for thepoint of interest 310 corresponding to the input request 306 and returna translation result 318 to the first device 102, the second device 106,or a combination thereof, such that the translation result 318 is to bedisplayed on the first display interface 206, the second displayinterface 234, or a combination thereof. The translation result 318refers to a value or a result returned based on the search for the pointof interest 310, in which the input request 306 is matched to the closesrelevant point or points of interest 310 based on the translationbetween the language of the input request 306 to the language of thesystem user's 304 current location 308. The first control unit 210, thesecond control unit 238, or a combination thereof can enable the searchfor the point of interest 310.

In one embodiment, the computing system 100 can search for the point ofinterest 310 on the second device 106 and return the translation result318 to the first device 102. The first device 102 can display thetranslation result 318 on the first display interface 206. In anotherembodiment, the computing system 100 can search for the point ofinterest 310 on the first device 102 and return the translation result318 to be displayed on the first display interface 206.

In another embodiment, the first audio interface 204, in conjunctionwith the first display interface 206, or by itself, can enable input ofthe input request 306 using audio commands. Audio commands areinstructions given to the computing system 100 using an audio input,such as voice, or other acoustic, mechanical, or electrical frequenciescorresponding to audible sound waves. For example, audio commands can bereceived through one or more sensors, microphones, transducers, or acombination thereof using the first audio interface 204. Similarly, theaudio commands can be received in a similar manner through the secondaudio interface 232 of the second device 106. The audio commands caninstruct the computing system 100 to search for the point of interest310 in the same manner as described above.

Continuing with the example, in one embodiment, the computing system 100can have a feedback mechanism allowing the system user 304 to give afeedback value 312 to the computing system 100 based on the translationresult 318. The feedback value 312 can represent the quality of thetranslation result 318 returned by the computing system 100. Forexample, in one embodiment, if the input request 306 is “Gasolinera” andthe computing system 100 returns a translation result 318 showing pointsof interest 310 as “gas stations,” the system user 304 can give afeedback value 312 indicating the translation result 318 wassatisfactory. Alternatively, if the input request is “Gasolinera” andthe computing system 100 returns a translation result 318 showing thepoint of interest 310 as “restaurants,” the system user 304 can give afeedback value 312 indicating the translation result 318 wasunsatisfactory.

The feedback value 312 can also be provided implicitly. For example, inone embodiment, when the translation result 318 is returned, the systemuser 304 can navigate to the translation result 318 and doing nothingelse. By doing so, the computing system 100 will know that the systemuser 304 was satisfied with the translation result 318.

The feedback value 312 can take a variety of forms. For example, thefeedback value can take the form of any ranking system, including butnot limited to, a numeric ranking system, a sliding scale rankingsystem, a binary input, a “good/bad” ranking, or a combination thereof.The feedback value 312 can be stored in the first storage unit 216, thesecond storage unit 240, or a combination thereof. The feedback value312 can be used by the computing system 100 to refine a futuretranslation result of a future input request for the input request 306.For example, in one embodiment, the feedback value 312 can be used totrain the computing system 100 as a part of a machine learning algorithmor deep learning algorithm, using a supervised or an unsupervisedmachine learning mechanism, where the feedback value 312 can be used toteach the computing system 100 to learn patterns and representations forthe input request 306 so that a future input request for the inputrequest 306 yields more accurate and relevant results and returns bettertranslation results 318.

Referring now to FIG. 4, therein is shown an exemplary control flow 400of the computing system 100. The computing system 100 can include areceiver module 402, a profile module 406, an input characterizationmodule 410, a location module 414, a map module 404, a determinationmodule 418, a first connotation database 426, a second connotationdatabase 432, a translation module 438, a display module 444, a feedbackmodule 446, and a storage module 450.

In one embodiment, the receiver module 402 can be coupled to the profilemodule 406 and the location module 414. The location module 414 can becoupled to the map module 404, the input characterization module 410,the translation module 438, and the determination module 418. Theprofile module 406 can be coupled to the determination module 418 andthe input characterization module 410. The input characterization module410 can be coupled to the determination module 418. The determinationmodule 418 can be coupled to the first connotation database 426, thetranslation module 438, and the display module 444. The translationmodule 438 can be coupled to the second connotation database 432 and thedisplay module 444. The display module 444 can be coupled to thefeedback module 446. The feedback module 446 can be coupled to thestorage module 450. The storage module can be coupled to the firstconnotation database 426 and the second connotation database 432. Thefirst connotation database 426 can be coupled to the second connotationdatabase 432.

The first connotation database 426 and the second connotation database432 are lexical databases of structured sets of terms and phrases of oneor more languages that are categorized as sets of cognitive synonymsexpressing a distinct concept. Terms and phrases are cognitivelysynonymous with another word if they refer to the same thingindependently of context. The first connotation database 426 and thesecond connotation database 432 can have the sets of cognitive synonymscategorized based on a machine learning algorithm or deep learningalgorithm, using a supervised or an unsupervised machine learningmechanism. The first connotation database 426 and the second connotationdatabase 432 can have the sets of cognitive synonyms grouped in avariety of ways. For example, the sets of cognitive synonyms can begrouped based on word associations, real world relationships andsub-relationships, a specific cultural context of words or phrases,location information, a time and date information, a hypernym (“is-a”)relationship, a meronym (“part-whole”) relationship, a sisternym(“like-a”) relationship, or a combination thereof.

The hypernym relationship describes relationships between cognitivesynonyms in which one term has a broader meaning and that more specificwords fall under or a superordinate to that term (i.e., “is-a”). Forexample, the term “color” is a hypernym of red. The meronym relationshipdescribes relationships between cognitive synonyms in which one termdenotes part of something which is used to refer to the whole of it(i.e., “part-whole”). For example, the term “faces” when used to meanpeople in the phrase “I see several familiar faces present” is a meronymof “people.” A sisternym relationship describes relationships betweencognitive synonyms in which one term refers to a concept that is similarto the concept expressed by another term but it not identical (i.e.,“like-a”). For example, the term “coffee shop” is a sisternym of “cafe.”

In one embodiment, for example, the first connotation database 426 andthe second connotation database 432 can group the terms “restaurant,”“gas station,” and “cafe” together because in some locals, for examplein the United States, each of a “restaurant,” “gas station,” and “cafe”are places where a person can obtain food, and therefore an inputrequest 306 for “Food” should return the translation result 318 showingrestaurants, gas stations, and cafes as relevant points of interest 310where a system user 304 can get food. In another embodiment, the phrases“pet store,” “zoo,” and “farm” can be grouped together because these areplaces where animals can be seen.

In one embodiment, the receiver module 402 can enable the receiving ofthe input request 306 for a point of interest 310, as described withrespect to FIG. 3. The receiver module 402 can pass control of the inputrequest 306 to the profile module 406, the location module 414, or acombination thereof.

Continuing with the example, if control is passed to the profile module406, the profile module 406 can analyze the input request 306 against auser profile 408, using the input characterization module 410 todetermine whether the input request 306 can be matched to an assigned ordesignated system user's language 314 that is assigned or designated ina user profile 408. The user profile 408 is a description or arepresentation of the system user 304. The user profile 408 can includeuser identification as information utilized for identifying the systemuser 304. For example, the user identification can include a name, agovernment-issued identification information, an account name oridentification, a contact information, physical features or traits ofthe system user 304, voice recognition meta-data of the system user 304,system user 304 preferences, assigned or designated system user'slanguages 314, or a combination thereof.

If the input characterization module 410 finds a match, the profilemodule 406, the input characterization module 410, or a combinationthereof can pass one or more indicators to the determination module 418indicating that the first connotation database 426 to be accessed whendetermining the first linguistic context 420 should be one withcognitive synonym sets assigned and associated with the system user'slanguage 314.

The one or more indicators refer to an associated symbolic name, whichcontains some known or unknown quantity of information referred to as avalue. For example, in one embodiment, if the system user's language 314is designated as “Mexican Spanish” and the input characterization module410 determines that the input request 306 is also input in “MexicanSpanish” by analyzing the syntax, words, phrases, or a combinationthereof of the input request 306, then a match is found and the profilemodule 406, the input characterization module 410, or a combinationthereof can pass a symbolic name such as “MX_SP” to the determinationmodule 418 indicating that the first connotation database 426 to beaccessed should contain cognitive synonym sets for the “Mexican Spanish”language.

Continuing with the example, in one embodiment, the receiver module 402can pass control of the input request 306 to the location module 414,either by itself or in conjunction with passing control of the inputrequest 306 to the profile module 406. The location module 414 can usethe first location unit 214, the second location unit 246, or acombination thereof to obtain the system user's 304 current location308. The location module 414 can analyze the input request 306 againstthe system user's 304 current location 308, using the inputcharacterization module 410 to determine whether the language of theinput request 306 can be matched to the language associated with thelocale of the system user's 304 current location 308. If a match isfound, the location module 414, the input characterization module 410,or a combination thereof can pass one or more indicators to thedetermination module 418 indicating that the first connotation database426 to be accessed when determining the first linguistic context 420should be one with cognitive synonym sets assigned and associated withthe system user's 304 current location 308. For example, in oneembodiment, if the input request 306 is determined to be input in“Mexican Spanish,” and the location module 414 determines that thesystem user's 304 current location 308 is in Mexico City, Mexico, thelocation module 414, the input characterization module 410, or acombination thereof can pass a symbolic name such as “MX_SP” to thedetermination module 418 indicating that the first connotation database426 to be accessed should contain cognitive synonym sets for the“Mexican Spanish” language.

In one embodiment, the location module 414 can obtain the system user's304 current location 308 using the first location unit 214, the secondlocation unit 246, or a combination thereof in conjunction with a mapmodule 404 holding map information of a variety of countries, regions,states, counties, cities, neighborhoods, blocks or a combinationthereof. The map module 404 can also contain information regardingpoints of interest 310 or can interface with a further databasecontaining information regarding points of interest 310.

The input characterization module 410 can allow the profile module 406,the location module 414, or a combination thereof to identify thelanguage of the input request 306 using one or more input requestcharacteristics 412. The input characterization module 410 can do so byanalyzing one or more input request characteristics 412 of the inputrequest 306 in order to categorize, determine, or otherwise identify thelanguage of the input request 306. For example, in one embodiment, theinput characterization module 410 can analyze the syntax of the inputrequest 306 and compare the syntax of the input request 306 to thesyntax for a set of known languages to determine the language of theinput request 306. In another embodiment, the input characterizationmodule 410 can analyze the language characters associated with the inputrequest 306 using, for example, an optical character recognition (OCR)technique, and compare the characters of the input request 306 to a setof known characters for known languages to determine the language of theinput request 306. In another embodiment, where the input request 306 isgiven through a voice command through the first audio interface 204, thesecond audio interface 232, or a combination thereof, the inputcharacterization module 410 can analyze the voice command by comparing asound or an audible signal to a set of known sounds, dialects, phonetictones, or a combination thereof of known languages to determine thelanguage of the input request 306. Analyzing the voice command can bedone using any number of techniques including but not limited to thoseused in speech recognition system based on Hidden Markov Models (HMM),dynamic time warping (DTW) based speech recognition, neural networks,end-to-end automatic speech recognition, or a combination thereof. Inanother embodiment, the input characterization module 410 can analyze asentence structure of the input request 306, a grammar of the inputrequest 306, a linguistic pattern of the input request 306, or anycombination thereof using text recognition techniques to determine thelanguage of the input request 306.

In another embodiment, if no system user language 314 is assigned ordesignated in the user profile 408, the input characterization module410 can analyze the input request 306 using the techniques describedabove in order to recognize the input request 306 language withoutreference to the user profile 408. In one embodiment, once the inputcharacterization module 410 is able to determine the language of theinput request 306, the input characterization module 410 can assign ordesignate the language to the user profile 408.

Continuing with the example, once control is passed to the determinationmodule 418, the determination module 418 can determine the firstlinguistic context 420 for the input request 306. The first linguisticcontext 420 indicates how the meaning of the input request 306 isunderstood by a system user 304 or by a person or persons who speak thesystem user's language 314. For example, in one embodiment, if the inputrequest 306 is “Gasolinera,” the first linguistic context 420 allows thecomputing system 100 to determine that the system user 304 would like tosearch for a “gas station” despite, for example, the system user 304being in an area that does not have “Mexican Spanish” as the primarylanguage of the locale, for example in Canada, and where the points ofinterest 310 are not designated in “Mexican Spanish.” Similarly, if theinput request 306 is “Happy Hour” the first linguistic context 420allows the computing system 100 to determine that the system user 304likely wants to look for businesses or establishments serving alcoholicbeverages within a certain time period. The first linguistic context 420enables the system user 304 to search for the points of interest 310using the input request 306 without the system user 304 needing to knowor understand the language associated with the system user's 304 currentlocation 308. Details of the first linguistic context 420 will bediscussed below. The second linguistic context 440 provides similarfunctionality as the first linguistic context 420. Details of the secondlinguistic context 440 will be discussed below

The determination module 418 can determine the first linguistic context420 using the first connotation database 426 and the one or moreindicators passed to the determination module 418 by the profile module406, the input characterization module 410, the location module 414, ora combination thereof. In one embodiment, the first linguistic context420 can be determined based on the language of the input request 306matching the language associated with the locale of the system user's304 current location 308. For example, if the language of input request306 matches the language associated with the system user's 304 currentlocation 308, the determination module 418 can access a firstconnotation database 426 associated with the matching language. Forexample, if the language of the input request 306 is “Mexican Spanish”and the current location 308 is Mexico City, Mexico, the firstconnotation database 426 to be accessed can be associated with andcontain cognitive synonym sets for the “Mexican Spanish” language.

Continuing with the example, where the language of the input request 306matches the language associated with the system user's 304 currentlocation 308 and the first connotation database 426 is determined, thefirst linguistic context 420 can be determined based on a mapping of theinput request 306 to the words, phrases, categories, or a combinationthereof contained in the first connotation database 426 that are similarto, identical to, related to or otherwise associated with the words,phrases, categories, associated with the input request 306. Thedetermination module 418 can assign the mapping by applying an identitytransform or a data mapping of the input request 306 to the firstconnotation database 426.

The identity transform or data mapping refer to a data transformationthat copies a source data from a first connotation database 426, thesecond connotation database 432, or a combination thereof to thedetermination module 418, the translation module 438, the firstconnotation database 426, the second connotation database 432, or acombination thereof.

For example, if the input request 306 is for “Gasolinera,” thedetermination module 418 can access the first connotation database 426associated with the “Mexican Spanish” language and search for words,terms, phrases, categories, or a combination thereof categorized in thefirst connotation database 426 and matching or associated with“Gasolinera.” Once found, the first connotation database 426 can returna first result 422 based on or containing the matching words, terms,phrases, categories, or a combination thereof to the determinationmodule 418 based on the identity transform or the data mapping. Thedetermination module 418 can assign the first linguistic context 420 asthe first result 422 and search for the point of interest 310 based onthe first linguistic context 420. The determination module 418 cansearch for the point of interest 310 using the location module 414 andthe map module 404 based on the first linguistic context 420 and returna translation result 318 associated with the search.

Continuing with the example, in another embodiment, if the one or moreindicators passed by the profile module 406, the input characterizationmodule 410, the location module 414, or a combination thereof indicatethat the language of the input request 306 does not match the languageassociated with the locale of the system user's 304 current location308, the determination module 418 can determine that the firstconnotation database 426 to be accessed should be associated with thelanguage associated with the input request 306. For example, in oneembodiment, if the language of the input request 306 is in “MexicanSpanish” and the current location 308 is Toronto, Canada, thedetermination module 418 can determine that the first connotationdatabase 426 to be accessed should be one associated with and containcognitive synonym sets for the “Mexican Spanish” language. Thedetermination module can also set a flag 424 indicating that thelanguage of the input request 306 and language associated with thelocale of the system user's 304 current location 308 do not match andthat further processing of the input request 306 is required by thetranslation module 438. Details regarding the further processing will bediscussed below. The flag 424 refers to a software or hardware mark,variable, condition, or a combination thereof that signals a particularcondition or status.

Continuing with the example, in one embodiment, if no further processingis required, the determination module 418 can pass control to thedisplay module 444 to display the translation result 318 on the firstdisplay interface 206, the second display interface 234, or acombination thereof.

In another embodiment, if further processing is required, thedetermination module 418 can pass control to the translation module 438.The translation module 438 can determine a second linguistic context 440for the input request 306. The second linguistic context 440 providessimilar functionality as the first linguistic context 420. Thetranslation module 438 can determine the second linguistic context 440in the same manner in which the first linguistic context 420 isdetermined, except using a second connotation database 432 associatedwith the language associated with the locale of system user's 304current location 308. For example, in one embodiment, if the systemuser's 304 current location 308 is New York City, U.S.A, the secondconnotation database 432 to be accessed is one associated with andcontaining cognitive synonym sets for the “U.S. English” language. Oncethe first connotation database 426 and the second connotation database432 are determined, the second linguistic context 440 can be determinedby the translation module 438 as a mapping of the words, phrases,categories, or a combination thereof associated with the firstlinguistic context 420 mapped to the equivalent words, phrases,categories, or a combination thereof in the second connotation database432.

The translation module 438 can assign the mapping by applying anidentity transform or a data mapping similar to that described abovewith respect to first connotation database 426, determination module418, and the input request 306 when a matching language is found.Details regarding the mapping will be discussed below.

Continuing with the example, once the mapping of the first linguisticcontext 420 to the second connotation database 432 is done, the secondconnotation database 432 can return a second result 442 to thetranslation module 438 based on the mapping. The translation module 438can assign the second linguistic context 440 as the second result 442and determine that the search for the point of interest 310 associatedwith the input request 306 should include a search for the words,phrases, categories, or a combination thereof associated with the secondlinguistic context 440. The translation module 438 can search for thepoint of interest 310 using the location module 414 and the map module404 based on the second linguistic context 440 and return a translationresult 318 associated with the search. Once the translation result 318is returned the translation module 438 can pass control to the displaymodule 444 to display the translation result 318 on the first displayinterface 206, the second display interface 234, or a combinationthereof.

Continuing with the example, in one embodiment, once the translationresult 318 is displayed on the first display interface 206, the seconddisplay interface 234 or a combination thereof, control can pass to thefeedback module 446 to allow the feedback value 312 to be received bythe computing system 100 in manner described in FIG. 3. The feedbackmodule 446 can enable the feedback value 312 to be received using thefirst display interface 206, the second display interface 234, the firstaudio interface 204, the second audio interface 232, or a combinationthereof. For example, in one embodiment, the feedback value 312 can bereceived by the computing system 100 through an entry from the firstdisplay interface 206, the second display interface 234, or acombination thereof. In another embodiment, the feedback module 446enable the feedback value 312 to be received by the computing system 100through a voice command through the first audio interface 204, thesecond audio interface 232, or a combination thereof. In anotherembodiment, the feedback module 446 can interface with a furtherdatabase to provide the feedback value 312.

Once received, in one embodiment, the feedback module 446 can pass thefeedback value 312 to the storage module 450. The storage module 450 canenable the storage of the feedback value 312 in the first storage unit216, the second storage unit 240, or a combination thereof. The feedbackvalue 312 can be used by the computing system 100 to refine a futuretranslation result of a future input request for the input request 306in a manner described in FIG. 3. For example, in one embodiment, thestorage module 450 can interface with the first connotation database426, the second connotation database 432, or a combination thereof tomodify the sets of cognitive synonyms in the first connotation database426, the second connotation database 432, or a combination thereof basedon the feedback value 312 to provide better results for a future inputrequest. The computing system 100 can achieve this modification by forexample, rearranging, re-categorizing, reclassifying, or otherwisechanging the word, phrase, term, or category associations in the firstconnotation database 426, the second connotation database 432, or acombination thereof to provide more relevant mappings or datatransformations for a future input request for the input request 306.

For example, in one embodiment, if the input request 306 is for“Gasolinera” and the translation result 318 displayed is for a“restaurant,” the feedback value 312 can indicate an unsatisfactoryresult. This unsatisfactory result can be passed to the firstconnotation database 426, the second connotation database 432, or acombination thereof such that the sets of cognitive synonyms in thefirst connotation database 426, the second connotation database 432, ora combination thereof can be rearranged, re-categorized, reclassified,or otherwise changed to disassociate “restaurants” from the term“Gasolinera” to provide more relevant mappings or data transformationsfor a future input request for the input request 306.

In one embodiment, the rearranging, re-categorizing, or reclassificationcan be based on the feedback module 446 monitoring the system user's 304actions subsequent receiving the unsatisfactory feedback 446. Forexample, in one embodiment, the feedback module 446 can monitor one ormore of the system user's 304 actions using one or more components ofthe computing system 100, for example sensors, microphones, transducers,the first location unit 214, the second location unit 246, or anycombination thereof. For example, in one embodiment, the feedback module444 can monitor the system user's 304 navigation path to determine wherethe system user's 304 destination ends during a trip in which the systemuser 304 searches for an input request 306, such that the address of thedestination and the address of the translation result 318 can becompared to determine relationships and attributes similar or differentbetween the two such that further categorizations or cognitivesynonymous relationships can be generated based on those relationshipsand attributes. For example, if the input request 306 is for “Food” anda “gas station” is not returned as a translation result 318 in a localewhere gas stations also serve food, the feedback module 446 can monitorthe system user's 304 navigation path and if the system user 304 ends upat a gas station, can determine that a “gas station” should becategorized under a search for “food” in the future when the inputrequest 306 is for “Food” in the particular locale. The firstconnotation database 426, the second connotation database 432, or acombination thereof can then be updated with the updated categorization,relationship, or attribute for future input requests associated with“Food” in that locale.

The computing system 100 has been described with module functions ororder as an example. The computing system 100 can partition the modulesdifferently or order the modules differently. For example, the firstsoftware 220 of FIG. 2 of the first device 102 can include the modulesfor the computing system 100. As a specific example, the first software220 can include the receiver module 402, the profile module 406, theinput characterization module 410, the location module 414, the mapmodule 404, the determination module 418, the first connotation database426, the second connotation database 432, the translation module 438,the display module 444, the feedback module 446, and the storage module450, and associated sub-modules included therein.

The first control unit 210 of FIG. 2 can execute the first software 220to operate the modules. For example, the first control unit 210 canimplement the receiver module 402, the profile module 406, the inputcharacterization module 410, the location module 414, the map module404, the determination module 418, the first connotation database 426,the second connotation database 432, the translation module 438, thedisplay module 444, the feedback module 446, and the storage module 450,and associated sub-modules included therein.

In another example of module partitions, the second software 244 of FIG.2 of the second device 106 can include the modules for the computingsystem 100. As a specific example, the second software 244 can includethe receiver module 402, the profile module 406, the inputcharacterization module 410, the location module 414, the map module404, the determination module 418, the first connotation database 426,the second connotation database 432, the translation module 438, thedisplay module 444, the feedback module 446, and the storage module 450,and associated sub-modules included therein.

The second control unit 238 of FIG. 2 can execute the second software244 to operate the modules. For example, the second control unit 238 canimplement the receiver module 402, the profile module 406, the inputcharacterization module 410, the location module 414, the map module404, the determination module 418, the first connotation database 426,the second connotation database 432, the translation module 438, thedisplay module 444, the feedback module 446, and the storage module 450,and associated sub-modules included therein.

The computing system 100 has been described with module functions ororder as an example. The computing system 100 can partition the modulesdifferently or order the modules differently.

The modules described in this application can be implemented asinstructions stored on a non-transitory computer readable medium to beexecuted by a first control unit 210, the second control unit 238, or acombination thereof. The non-transitory computer medium can include thefirst storage unit 216, the second storage unit 240, or a combinationthereof. The non-transitory computer readable medium can includenon-volatile memory, such as a hard disk drive, non-volatile randomaccess memory (NVRAM), solid-state storage device (SSD), compact disk(CD), digital video disk (DVD), or universal serial bus (USB) flashmemory devices. The non-transitory computer readable medium can beintegrated as a part of the computing system 100 or installed as aremovable portion of the computing system 100.

Referring now to FIG. 5, therein is shown an exemplary representation ofa cognitive synonym space 500 for the computing system 100.Specifically, FIG. 5 shows the cognitive synonym space 500 for the firstconnotation database 426, the second connotation database 432, or acombination thereof. The cognitive synonym space 500 represents howwords, terms, phrases, categories, or a combination thereof in the firstconnotation database 426, the second connotation database 432, or acombination thereof are grouped and mapped to one another as cognitivesynonym sets. FIG. 5 represents only one embodiment for a cognitivesynonym space 500. The example used in FIG. 5 is for the input request306 “Meal.” Cognitive synonym spaces 500 for other input requests 306can be represented similarly.

Continuing with the example, in one embodiment, assuming the inputrequest 306 is for “Meal,” the cognitive synonym space 500 can includeone or more measures that allow the determination module 418, thetranslation module 438, the first connotation database 426, the secondconnotation database 432, or a combination thereof to perform theidentity transform or the data mapping for the input request 306, suchthat the first linguistic context 420, the second linguistic context440, or a combination thereof can be determined across one or morelanguages. The one or more measures can be represented as one or morevariables, meta-data, parameters, or a combination thereof in the firstconnotation database 426, the second connotation database 432, or acombination thereof.

For example, for the input request 306 “Meal,” the cognitive synonymspace 500 can include one or more variables, meta-data, parameters, or acombination thereof that allows the determination module 418, thetranslation module 438, the first connotation database 426, the secondconnotation database 432, or a combination thereof to map the inputrequest 306 to words, terms, phrases, or categories associated with“Meal” in the first connotation database 426, the second connotationdatabase 432, or a combination thereof. For the input request 306“Meal,” these can include, for example, a weight measure 506, aprobability measure 502, and a time measure 504. Other variables,meta-data, or parameters can be used and the aforementioned areexemplary, and are set forth for brevity of discussion and to betterexplain the example discussed in FIG. 5.

Continuing with the example, for the input request 306 “Meal,” theweight measure 506 can refer to a degree, a quantity, a measure, or acombination thereof of the input request 306. For example, a meal cancontain a degree representing a “heaviness” of the meal which isassociated with how much food is typically eaten during a meal. Forexample, meals can be categorized from “Very Light” representing thatvery little food is typically eaten during that meal, to “Very Heavy”representing that a large quantity of food is typically eaten duringthat meal. Examples of “Very Light” meals can include snacks orbreakfasts. Examples of “Very Heavy” meals can include dinners, lunches,or feasts. The weight measure 506 can vary amongst different connotationdatabases associated with different languages. For example, connotationdatabases associated with languages in which the culture associated withthat language considers breakfast a “Very Heavy” meal can have theweight measure 506 categorized differently than connotation databasesassociated with languages in which the culture associated with thatlanguage considers breakfast as a “Very Light” meal.

The time measure 504 can refer to a time or date associated with theinput request 306. For example, for the input request 306 “Meal,” thetime measure 504 can include times or dates when the meal is typicallyeaten. For example, dinners can be categorized as typically being eatenin the evenings between 5:00 pm-8:00 pm and breakfasts can becategorized as typically eaten before noon. In another embodiment, theinput request 306 “Christmas Dinner” can be categorized as typicallybeing eaten on or around December 25 of the calendar year in aconnotation database associated with “U.S. English.” The time measure504 can vary amongst different connotation databases associated withdifferent languages similar to how the weight measure 506 can differamongst different connotation databases.

The probability measure 502 can refer to the probability that a certainattribute of the input request 306 will be present. Continuing with theexample, in one embodiment, for the input request 306 “Meal,” theprobability measure 502 can represent the probability that the meal willcontain, for example, sweets. Other probability measures 502 can be usedsuch as those indicating the probability that the meal will contain, forexample, “meat” or a “dessert.” In one embodiment, the probabilitymeasure 502 can be based on a numerical value range. In one embodiment,the numerical value range range can include a range from 0.0-1.0indicating how probable it is that the attribute of the input request306 will be present, with 0.0 representing zero to little probabilityand 1.0 representing an absolute certainty or a high probability. Inanother embodiment, the probability measure 502 can be represented usingcategorizations, for example, “Highly Probable,” “Probable,” “NotProbable.” For example, in the current example where the probability ofa meal containing sweets is considered, for meals such as dinner orlunch, the probability measure 502 can be a lower probability while formeals such as snacks the probability measure can be a higherprobability. The probability measure 502 can vary amongst differentconnotation databases associated with different languages similar to howthe weight measure 506 can differ amongst different connotationdatabases.

Continuing with the example, in one embodiment, each word, term, phrase,category, or combination thereof contained a connotation database can bemapped to a point 508 in the cognitive synonym space 500 based on theone or more measures for each word, term, phrase, or category. In thecurrent example, because the cognitive synonym space 500 consists ofthree points of measure which are the weight measure 506, theprobability measure 502, and the time measure 504, the cognitive synonymspace can form a three-dimensional space. In one embodiment, thethree-dimensional space can be represented with a multi-axis graphrepresenting an (X,Y,Z) axis. The words, terms, phrases, categories, ora combination thereof can be set to a point 508 in the three-dimensionalspace by connecting the one or more measures along each of their valueson each axis. As a result, words, terms, phrases, categories, or acombination thereof with similar values for their one or more measurescan be grouped together in clusters within the cognitive synonym space500. The clusters can form the bases for word, phrase, term, or categorygroupings. The computing system 100 can use the words, terms, phrases,categories, or a combination thereof to determine the first linguisticcontext 420, the second linguistic context 440, or a combination thereofand to generate and return the first result 422, the second result 442,or a combination thereof.

For example, in one of the embodiments previously mentioned with respectto FIG. 4, if the input request 306 matches the language associated withthe system user's 304 current location 308, the first connotationdatabase 426 is determined and the first linguistic context 420 can bedetermined based on a mapping of the input request 306 to the words,phrases, categories, or a combination thereof contained in the firstconnotation database 426 that are similar to, identical to, related to,grouped closely to, or otherwise associated with the words, phrases,categories, associated with the input request 306. Once mapped, thefirst connotation database 426 can assign the mapped result as the firstresult 422. For example, assuming the input request 306 is for “Dinner”and the system user's 304 current location 308 is New York City, USA.The first connotation database 426 is determined to be one associatedwith “U.S. English.” The computing system 100 can then look for words,phrases, or categories related to “Dinner” and return mapped words,phrases, or categories as the first result 422. In the aforementionedexample, the mapping of the words, phrases, or categories can be doneone-to-one and a direct lookup of words, phrases, terms, or categoriesof the first connotation database 426 can be done because the languageof the input request 306 is the same as the language associated with thefirst connotation database 426 and therefore the same words or phrasescan be searched for.

In another embodiment previously mentioned with respect to FIG. 4, ifthe language of the input request 306 does not match with the systemuser's 304 current location 308, the computing system 100 will need tomap the first linguistic context 420 associated with the firstconnotation database 426 to the second linguistic context 440 associatedwith the second connotation database 432 such that the translationmodule 438 can search for the input request 306 using the equivalentterms and in the same context between the first connotation database 426and the second connotation database 432. For example, if the inputrequest 306 is for “Dinner” and the system user's 304 current location308 is in Mexico City, Mexico, then the first connotation database canbe associated with “U.S. English” while the second connotation database432 can be associated with “Mexican Spanish.” Thus, the term “Dinner” inthe first connotation database 426 must be mapped to the equivalent termin the second connotation database 432 which is “Cena.” In oneembodiment, the mapping can be done using a distance calculation betweenwords, terms, phrases, or categories in the first connotation database426 and the second connotation database 432. In one embodiment thedistance calculation can be done by taking the point 508 associated withthe word, term, phrase, or category in the first connotation database426 and finding the equivalent point 508 in the second connotationdatabase 432. The computing system 100 can then find words, terms,phrases, or categories, in the second connotation database close to ornearby the point in the second connotation database 432. The computingsystem 100 can then measure the distances 510 between the equivalentpoint 508 in the second connotation database 432 and the various words,terms, phrases, or categories. The smaller the distances 510 between theequivalent point 508 and the words, terms, phrases, or categories in thesecond connotation database 432, the more likely the word, term, phrase,or category in the second connotation database 432 is related to orequivalent to the word, term, phrase, or category of the firstconnotation database 426. In this embodiment and example, the assumptionis that the one or more measures are the same amongst the one or moreconnotation databases such that points 508 can be mapped equivalently.

An example of the distance calculations is as follows. As shown in FIG.5, which depicts the aforementioned embodiment, the input request 306can be “Dinner,” which is associated with the first connotation database426. The second connotation database 432 can be associated with the“Mexican Spanish” language and can contain the terms “Cena,” which isthe equivalent for “Dinner” and the word “Desayuno” which is theequivalent for “Breakfast.” The distance “d1” is the distance betweenthe equivalent point 508 for “Dinner” in the second connotation database432 and the word “Cena” which has similar or equivalent measures as thatfor “Dinner.” The distance “d2” is the distance between the equivalentpoint 508 for “Dinner” in the second connotation database 432 and theword “Desayuno” which has different measures as that for “Dinner.”Because “d1” is smaller and thus closer to the equivalent point 508 than“d2,” the second connotation database will choose the word “Cena” as amapping to the word “Dinner” and return “Cena” as the second result 442.

While the aforementioned example and embodiment, indicates a single wordmapping, the benefits of the invention can be readily realized whensearching for more complex phrases or words that do not have equivalentsamongst languages. In such situations, words, phrases, terms, orcategories with no equivalents can still be mapped based on the one ormore measures and the mapping techniques described herein.

It has been discovered that the mapping techniques described hereinprovides increased usability and accessibility for searching for pointsof interest 310 in an area where the system user's language 314 isdifferent than the language of the system user's 304 current location308. The computing system 100 with the first connotation database 426,the second connotation database 432, the first linguistic context 420,and the second linguistic context 432 can provide increase inrecognition of natural language or speech patterns such that bettertranslations can be made across languages.

It has been discovered that the computing system 100 with the firstconnotation database 426, the second connotation database 432, the firstlinguistic context 420, and the second linguistic context 432 using themapping techniques disclosed herein can provide increased probability ofidentifying points of interest 310 relevant to the current situation orcondition of the system user 304 without the system user 304 knowing thelanguage associated with the system user's 304 current location 308. Asa result, the computer system 100 can lessen the probability that asystem user 304 will not find a desired point of interest 310 when theyare in a geographic area in which the language of the locate isdifferent from the system user's language 314 or the language of theinput request 306.

Referring now to FIG. 6, therein is shown a flow chart of a method 600of operation of a computing system in a further embodiment of thepresent invention. The method 600 includes: receiving 602 an inputrequest 306 for a point of interest 310; determining 604 a firstlinguistic context 420 for the input request 306 based on one or moreinput request characteristics 412, a user profile 408, a location 308,and a first connotation database 426; translating 608 the input request306 to a second linguistic context 440 based on a translation flag 424and a second connotation database 432, wherein the second connotationdatabase 432 is mapped to the first connotation database 426; anddisplaying 610 a translation result 318 for the input request 306 basedon the first linguistic context 420 or the second linguistic context440.

The resulting method, process, apparatus, device, product, and system iscost-effective, highly versatile, and accurate, and can be implementedby adapting known components for ready, efficient, and economicalmanufacturing, application, and utilization. Another important aspect ofan embodiment of the present invention is that it valuably supports andservices the historical trend of reducing costs, simplifying systems,and increasing performance.

These and other valuable aspects of the embodiments of the presentinvention consequently further the state of the technology to at leastthe next level. While the invention has been described in conjunctionwith a specific best mode, it is to be understood that manyalternatives, modifications, and variations will be apparent to thoseskilled in the art in light of the descriptions herein. Accordingly, itis intended to embrace all such alternatives, modifications, andvariations that fall within the scope of the included claims. Allmatters set forth herein or shown in the accompanying drawings are to beinterpreted in an illustrative and non-limiting sense.

What is claimed is:
 1. A computing system comprising: a control unitconfigured to: receive an input request for a point of interest;determine a first linguistic context for the input request fordetermining a meaning of the input request based on one or more inputrequest characteristics, a user profile, a current location of a systemuser, and a first connotation database including sets of cognitivesynonyms expressing a distinct concept, including differences between alanguage of the input request and a language of the current locationwithout the system user knowledge of the language of the currentlocation; translate the input request to a second linguistic contextbased on a translation flag and a second connotation database, whereinthe second connotation database is mapped to the first connotationdatabase using the sets of cognitive synonyms; and a user interface,coupled to the control unit, configured to display a translation resultfor the input request based on the first linguistic context or thesecond linguistic context.
 2. The system as claimed in claim 1 whereinthe first connotation database and the second connotation databasecomprise one or more categories for classifying language informationbased on one or more measures.
 3. The system as claimed in claim 2wherein the one or more categories for classifying language informationare based on one or more of a culture, a geography, or a time period. 4.The system as claimed in claim 1 wherein translating the input requestto the second linguistic context based on the translation flag is basedon one or more of a hypernym relationship, a meronym relationship, or asisternym relationship.
 5. The system as claimed in claim 1 wherein thecontrol unit is further configured to receive a feedback value based onthe translation result, wherein the feedback value is for refining afuture result for a future input request for the input request; andfurther comprising: a storage unit, coupled to the control unit, forstoring the feedback value.
 6. A computing system comprising: a firstcontrol unit configured to: receive an input request for a point ofinterest; determine a first linguistic context for the input request fordetermining a meaning of the input request based on one or more inputrequest characteristics, a user profile, a current location of a systemuser, and a first connotation database including sets of cognitivesynonyms expressing a distinct concept, including differences between alanguage of the input request and a language of the current locationwithout the system user knowledge of the language of the currentlocation; a communication unit, coupled to the first control unit,configured to: send a transmission of the input request to a secondcontrol unit based on a translation flag; receive a translation resultfor the input request based on a translation of the input request to asecond linguistic context by the second control unit; the second controlunit, coupled to the communication unit, configured to translate theinput request to the second linguistic context based on the translationflag and a second connotation database, wherein the second connotationdatabase is mapped to the first connotation database using the sets ofcognitive synonyms; and a user interface, coupled to the first controlunit, configured to display a translation result for the input requestbased on the first linguistic context or the second linguistic context.7. The computing system as claimed in claim 6 wherein the firstconnotation database and the second connotation database comprise one ormore categories for classifying language information based on one ormore measures.
 8. The computing system as claimed in claim 7 wherein theone or more categories for classifying language information are based onone or more of a culture, a geography, or a time period.
 9. Thecomputing system as claimed in claim 6 wherein translating the inputrequest to the second linguistic context based on the translation flagis based on one or more of a hypernym relationship, a meronymrelationship, or a sisternym relationship.
 10. The computing system asclaimed in claim 6 wherein: the first control unit or the second controlunit is further configured to receive a feedback value based on thetranslation result for refining a future result for a future inputrequest for the input request; and further comprising: a storage unit,coupled to the first control unit or the second control unit, forstoring the feedback value.
 11. A method of operating a computing systemcomprising: receiving an input request for a point of interest;determining a first linguistic context for the input request fordetermining a meaning of the input request based on one or more inputrequest characteristics, a user profile, a current location of a systemuser, and a first connotation database including sets of cognitivesynonyms expressing a distinct concept, including differences between alanguage of the input request and a language of the current locationwithout the system user knowledge of the language of the currentlocation; translating the input request to a second linguistic contextbased on a translation flag and a second connotation database, whereinthe second connotation database is mapped to the first connotationdatabase using the sets of cognitive synonyms; and displaying atranslation result for the input request based on the first linguisticcontext or the second linguistic context.
 12. The method as claimed inclaim 11 further comprising classifying language information in thefirst connotation database and the second connotation database using oneor more categories, wherein the classification is based on one or moremeasures.
 13. The method as claimed in claim 12 wherein classifyinglanguage information in the one or more categories is based on one ormore of a culture, a geography, or a time period.
 14. The method asclaimed in claim 11 wherein translating the input request to the secondlinguistic context based on the translation flag is based on one or moreof a hypernym relationship, a meronym relationship, or a sisternymrelationship.
 15. The method as claimed in claim 11 further comprising:receiving a feedback value based on the translation result, wherein thefeedback value is for refining a future result for a future inputrequest for the input request; and storing the feedback value.
 16. Themethod as claimed in claim 11 further comprising: sending a transmissionof the input request based on the translation flag; and receiving thetranslation result for the input request based on the translation of theinput request to the second linguistic context.
 17. A non-transitorycomputer readable medium including instructions for operating acomputing system comprising: receiving an input request for a point ofinterest; determining a first linguistic context for the input requestfor determining a meaning of the input request based on one or moreinput request characteristics, a user profile, a current location of asystem user, and a first connotation database including sets ofcognitive synonyms expressing a distinct concept, including differencesbetween a language of the input request and a language of the currentlocation without the system user knowledge of the language of thecurrent location; translating the input request to a second linguisticcontext based on a translation flag and a second connotation database,wherein the second connotation database is mapped to the firstconnotation database using the sets of cognitive synonyms; anddisplaying a translation result for the input request based on the firstlinguistic context or the second linguistic context.
 18. Thenon-transitory computer readable medium in claim 17 with instructionsfurther comprising classifying language information in the firstconnotation database and the second connotation database using one ormore categories, wherein the classification is based on one or moremeasures.
 19. The non-transitory computer readable medium in claim 18with instructions wherein classifying language information in the one ormore categories is based on one or more of a culture, a geography, or atime period.
 20. The non-transitory computer readable medium in claim 18with instructions wherein translating the input request to the secondlinguistic context based on the translation flag is based on one or moreof a hypernym relationship, a meronym relationship, or a sisternymrelationship.